- Location
- Bengaluru, Karnataka, India · published
- Type
- Full-time
- Department
- Education
- Source
- Workable
Description
Role purpose
As a Credit Data Scientist, you’ll use data, feature engineering and experimentation to improve credit decisioning and portfolio performance across our lending products and markets. You’ll work end-to-end from data exploration through to production-aligned features, monitoring and impact measurement.
Key responsibilities
· Analyse customer, bureau, transactional and repayment data to identify drivers of risk, loss, approval rates and customer outcomes.
· Build and iterate credit risk features and model inputs (behavioural signals, affordability proxies, stability-tested transformations), partnering closely with senior modellers and engineering.
· Contribute to development and improvement of predictive models using modern machine learning approaches, with a focus on robustness, stability and deployability.
· Design, run and evaluate credit policy experiments (cut-offs, limits, pricing/risk trade-offs, segment strategies), including post-implementation reviews.
· Develop monitoring for model/policy performance and feature health (drift, stability, segment performance, data quality checks).
· Support portfolio analytics: vintage analysis, roll-rates, migration, early warning indicators, collections funnel analytics, and loss driver deep-dives.
· Work with Data/Engineering to improve data definitions, quality, lineage and reproducible pipelines; document feature logic and assumptions.
· Contribute to governance documentation (model inputs, feature catalogues, monitoring evidence, change logs).